In January 2014, an international meeting sponsored by the International Life Sciences Institute/Health and Environmental Sciences Institute and the Canadian Food Inspection Agency titled “Genetic Basis of Unintended Effects in Modified Plants” was held in Ottawa, Canada, bringing together over 75 scientists from academia, government, and the agro-biotech industry. The objectives of the meeting were to explore current knowledge and identify areas requiring further study on unintended effects in plants and to discuss how this information can inform and improve genetically modified (GM) crop risk assessments. The meeting featured presentations on the molecular basis of plant genome variability in general, unintended changes at the molecular and phenotypic levels, and the development and use of hypothesis-driven evaluations of unintended effects in assessing conventional and GM crops. The development and role of emerging “omics” technologies in the assessment of unintended effects was also discussed. Several themes recurred in a number of talks; for example, a common observation was that no system for genetic modification, including conventional methods of plant breeding, is without unintended effects. Another common observation was that “unintended” does not necessarily mean “harmful”. This paper summarizes key points from the information presented at the meeting to provide readers with current viewpoints on these topics.Electronic supplementary materialThe online version of this article (doi:10.1007/s11248-015-9867-7) contains supplementary material, which is available to authorized users.

The Organization for Economic Co-operation and Development (OECD) recommends the measurement of specific plant components for compositional assessments of new biotechnology-derived crops. These components include proximates, nutrients, antinutrients, and certain crop-specific secondary metabolites. A considerable literature on the natural variability of these components in conventional and biotechnology-derived crops now exists. Yet the OECD consensus also suggests measurements of any metabolites that may be directly associated with a newly introduced trait. Therefore, steps have been initiated to assess natural variation in metabolites not typically included in the OECD consensus but which might reasonably be expected to be affected by new traits addressing, for example, nutritional enhancement or improved stress tolerance. The compositional study reported here extended across a diverse genetic range of maize hybrids derived from 48 inbreds crossed against two different testers. These were grown at three different, but geographically similar, locations in the United States. In addition to OECD analytes such as proximates, total amino acids and free fatty acids, the levels of free amino acids, sugars, organic acids, and selected stress metabolites in harvested grain were assessed. The major free amino acids identified were asparagine, aspartate, glutamate, and proline. The major sugars were sucrose, glucose, and fructose. The most predominant organic acid was citric acid, with only minor amounts of other organic acids detected. The impact of genetic background and location was assessed for all components. Overall, natural variation in free amino acids, sugars, and organic acids appeared to be markedly higher than that observed for the OECD analytes.

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Ground beef patties (75% lean) containing synthetic antioxidants, or Fenugreek (Trigonella foenumgraecum) extracts were cooked to internal temperature 70ЊC, and evaluated for storage stability at 4ЊC. Thiobarbituric acid values of raw or cooked samples containing fenugreek extracts were lower than controls (PϽ0.05). Fenugreek extracts delayed the induction period of oxidative rancidity. No differences were observed in psychrotrophic bacterial counts, and samples containing fenugreek extracts had lower Hunterlab ''a' ' and higher ''b'' values. Samples with Fenugreek extracts had better oxidative stability and Fenugreek may be a promising natural antioxidant source.

Plant breeders face multiple global challenges that affect food security, productivity, accessibility, and nutritional quality. One major challenge for plant breeders is developing environmentally resilient crop cultivars in response to rapid shifts in cultivation conditions and resources due to climate change. Plant breeders rely on different crop genetic resources, breeding tools, and methods to incorporate genetic diversity into commercialized cultivars. Breeders use genetic diversity to develop new cultivars with improved agronomics, such as higher yield, biotic and abiotic stress tolerance, and to improve the nutritional quality of foods for a growing world population. Plant breeders perform the essential task of strategic integration of new genetic diversity while preserving important economic traits of individual crops such as relative maturity (maize, Zea mays L.), fruit type (tomato, Lycopersicon esculentum Mill.), plant type (lettuce Lactuca sativa L.), and habitat type (canola, Brassica napus L.) that are highly specialized for specific consumer preferences or market needs. This review provides an industry perspective on how genetic diversity is incorporated for crop improvement by (a) using a real-life example to highlight the vast amount of genetic diversity that exists in plants, (b) providing a conceptual example to illustrate strategic challenges a breeder faces while incorporating diversity, (c) describing how and why it can a decade or more to incorporate diversity into commercialized cultivars, even when advanced tools and technologies are used, and (d) sharing factors that plant breeders consider when applying various tools, including genome editing, at different stages of plant breeding.

Understanding the impact of genetic diversity on crop biochemical composition is a prerequisite to the interpretation and potential relevance of biochemical differences experimentally observed between genotypes. This is particularly important in the context of comparative safety assessments for crops developed by new technologies such as genetic engineering. To interrogate the natural variability of biochemical composition, grain from seven maize hybrids grown at four geographically distinct sites in Europe was analyzed for levels of proximates (fat, protein, moisture, ash, and carbohydrates), fiber, amino acids, fatty acids, four vitamins, nine minerals, and secondary metabolites. Statistical evaluation of the compositional data at the p < 0.05 level compared each hybrid against every other hybrid (head-to-head) for all analytes at each site and then across all sites to understand the factors contributing to variability. Of the 4935 statistical comparisons made in this study, 40% (1986) were found to be significant. The magnitude of differences observed, as a percent, ranged between 0.84 and 149% when all individual sites and the combined sites were considered. The large number of statistically significant differences in the levels of these analytes between seven commercial hybrids emphasizes the importance of genetic background and environment as determinants of the biochemical composition of maize grain, reflects the inherent natural variability in those analytes across a representative sampling of maize hybrids, and provides a baseline of the natural range of these nutritional and antinutritional components in maize for comparative compositional assessments.

Site-directed nucleases (SDNs) used for targeted genome editing are powerful new tools to introduce precise genetic changes into plants. Like traditional approaches, such as conventional crossing and induced mutagenesis, genome editing aims to improve crop yield and nutrition. Next-generation sequencing studies demonstrate that across their genomes, populations of crop species typically carry millions of single nucleotide polymorphisms and many copy number and structural variants. Spontaneous mutations occur at rates of ;10 28 to 10 29 per site per generation, while variation induced by chemical treatment or ionizing radiation results in higher mutation rates. In the context of SDNs, an off-target change or edit is an unintended, nonspecific mutation occurring at a site with sequence similarity to the targeted edit region. SDN-mediated offtarget changes can contribute to a small number of additional genetic variants compared to those that occur naturally in breeding populations or are introduced by induced-mutagenesis methods. Recent studies show that using computational algorithms to design genome editing reagents can mitigate off-target edits in plants. Finally, crops are subject to strong selection to eliminate off-type plants through well-established multigenerational breeding, selection, and commercial variety development practices. Within this context, off-target edits in crops present no new safety concerns compared to other breeding practices. The current generation of genome editing technologies is already proving useful to develop new plant varieties with consumer and farmer benefits. Genome editing will likely undergo improved editing specificity along with new developments in SDN delivery and increasing genomic characterization, further improving reagent design and application. PLANT GENETIC VARIABILITY Genetic differences between individuals are the basis of adaptation and evolution. Plant breeding, as a form of directed evolution, has a long history of using genetic diversity for crop improvement. During the process of crop domestication, humans selected individual plants with favorable traits that resulted from novel mutations or standing variation in the ancestral species. The process of selecting plant varieties with favorable characteristics for cultivation and consumption continues to the present day. Modern plant breeding is a more directed process than the crop improvement that occurred through the history and prehistory of most

Commercial‐scale plant breeding is a complex process in which new crop varieties are continuously being developed to improve yield and agronomic performance over current varieties. A wide array of naturally occurring genetic changes are sources of new characteristics available to plant breeders. During conventional plant breeding, genetic material is exchanged that has the potential to beneficially or adversely affect plant characteristics. For this reason, commercial‐scale breeders have implemented extensive plant selection practices to identify the top‐performing candidates with the desired characteristics while minimizing the advancement of unintended changes. Selection practices in maize (Zea mays L.) breeding involve phenotypic assessments of thousands of candidate lines throughout hundreds of different environmental conditions over many years. Desirable characteristics can also be introduced through genetic modification. For genetically modified (GM) crops, molecular analysis is used to select transformed plants with a single copy of an intact DNA insert and without disruption of endogenous genes. All the while, GM crops go through the same extensive phenotypic characterization as conventionally bred crops. Data from both conventional and GM maize breeding programs are presented to show the similarities between these two processes.